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Attention All Surgical Pathologists: Algorithms for Automated Primary Diagnosis of Digital Pathology Images Likely to Gain Regulatory Clearance in Near Future

Jun 14, 2021 | Clinical Laboratory Middleware, Informatics, Analytics, Digital Pathology, Instruments & Equipment, International Laboratory News, Laboratory Instruments & Laboratory Equipment, Laboratory News, Laboratory Operations, Laboratory Pathology

Hello primary diagnosis of digital pathology images via artificial intelligence! Goodbye light microscopes!

Digital pathology is poised to take a great leap forward. Within as few as 12 months, image analysis algorithms may gain regulatory clearance in the United States for use in primary diagnosis of whole-slide images (WSIs) for certain types of cancer. Such a development will be a true revolution in surgical pathology and would signal the beginning of the end of the light microscope era.

A harbinger of this new age of digital pathology and automated image analysis is a press release issued last week by Ibex Medical Analytics of Tel Aviv, Israel. The company announced that its Galen artificial intelligence (AI)-powered platform for use in the primary diagnosis of specific cancers will undergo an accelerated review by the Food and Drug Administration (FDA).

FDA’s ‘Breakthrough Device Designation’ for Pathology AI Platform

Ibex stated that “The FDA’s Breakthrough Device Designation is granted to technologies that have the potential to provide more effective treatment or diagnosis of life-threatening diseases, such as cancer. The designation enables close collaboration with, and expedited review by, the FDA, and provides formal acknowledgement of the Galen platform’s utility and potential benefit as well as the robustness of Ibex’s clinical program.”

“All surgical pathologists should recognize that, once the FDA begins to review and clear algorithms capable of using digital pathology images to make an accurate primary diagnosis of cancer, their daily work routines will be forever changed,” stated Robert L. Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report. “Essentially, as FDA clearance is for use in clinical care, pathology image analysis algorithms powered by AI will put anatomic pathology on the road to total automation.

“Clinical laboratories have seen the same dynamic, with CBCs (complete blood counts) being a prime example. Through the 1970s, clinical laboratories employed substantial numbers of hematechnologists [hematechs],” he continued. “Hematechs used a light microscope to look at a smear of whole blood that was on a glass slide with a grid. The hematechs would manually count and record the number of red and white blood cells.

“That changed when in vitro diagnostics (IVD) manufacturers used the Coulter Principle and the Coulter Counter to automate counting the red and white blood cells in a sample, along with automatically calculating the differentials,” Michel explained. “Today, only clinical lab old-timers remember hematechs. Yet, the automation of CBCs eventually created more employment for medical technologists (MTs). That’s because the automated instruments needed to be operated by someone trained to understand the science and medicine involved in performing the assay.”

Primary Diagnosis of Cancer with an AI-Powered Algorithm

Surgical pathology is poised to go down a similar path. Use of a light microscope to conduct a manual review of glass slides will be supplanted by use of digital pathology images and the coming next generation of image analysis algorithms. Whether these algorithms are called machine learning, computational pathology, or artificial intelligence, the outcome is the same—eventually these algorithms will make an accurate primary diagnosis from a digital image, with comparable quality to a trained anatomic pathologist.

How much of a threat is automated analysis of digital pathology images? Computer scientist/engineer Ajit Singh, PhD, a partner at Artiman Ventures and an authority on digital pathology, believes that artificial intelligence is at the stage where it can be used for primary diagnosis for two types of common cancer: One is prostate cancer, and the other is dermatology.

Ajit Singh, PhD speaking at the Executive War College

On June 17, Ajit Singh, PhD (above), Partner at Artiman Ventures, will lead a special webinar and roundtable discussion for all surgical pathologists and their practice administrators on the coming arrival of artificial intelligence-powered algorithms to aid in the primary diagnosis of certain cancers. Regulatory approval for such solutions may happen by the end of this year. Such a development would accelerate the transition from light microscopes to a fully digital pathology workflow. Singh is shown above addressing the 2018 Executive War College. (Photo copyright: The Dark Report.)

“This is particularly true of prostate cancer, which has far fewer variables compared to breast cancer,” stated Singh in an interview published by The Dark Report in April. (See TDR, “Is Artificial Intelligence Ready for First Use in Anatomic Pathology?” April 12, 2021.)

“It is now possible to do a secondary read, and even a first read, in prostate cancer with an AI system alone. In cases where there may be uncertainty, a pathologist can review the images. Now, this is specifically for prostate cancer, and I think this is a tremendous positive development for diagnostic pathways,” he added.

Use of Digital Pathology with AI-Algorithms Changes Diagnostics

Pathologists who are wedded to their light microscopes will want to pay attention to the impending arrival of a fully digital pathology system, where glass slides are converted to whole-slide images and then digitized. From that point, the surgical pathologist becomes the coach and quarterback of an individual patient’s case. The pathologist guides the AI-powered image analysis algorithms. Based on the results, the pathologist then orders supplementary tests appropriate to developing a robust diagnosis and guiding therapeutic decisions for that patient’s cancer.

In his interview with The Dark Report, Singh explained that the first effective AI-powered algorithms in digital pathology will be developed for prostate cancer and skin cancer. Both types of cancer are much less complex than, say, breast cancer. Moreover, the AI developers have decades of prostate cancer and melanoma cases where the biopsies, diagnoses, and downstream patient outcomes create a rich data base from which the algorithms can be trained and tuned.

To help surgical pathologists, pathologist-business leaders, and pathology group practice administrators understand the rapid developments in AI-powered digital pathology analysis, Dark Daily is conducting “Clinical-Grade Artificial Intelligence (AI) for Your Pathology Lab: What’s Ready Now, What’s Coming Soon, and How Pathologists Can Profit from Its Use,” on Thursday, June 17, 2021, from 1:00 PM to 2:30 PM EDT.

This webinar is organized as a roundtable discussion so participants can interact with the expert panelists. The Chair and Moderator is Ajit Singh, PhD, Adjunct Professor at the Stanford School of Medicine and Partner at Artiman Ventures.

Panelists for June 17 webinar, Clinical-Grade Artificial Intelligence (AI) for Your Pathology Lab: What’s Ready Now, What’s Coming Soon, and How Pathologists Can Profit from Its Use

The panelists (above) represent academic pathology, community hospital pathology, and the commercial sector. They are:

Because the arrival of automated analysis of digital pathology images will transform the daily routine of every surgical pathologist, it would be beneficial for all pathology groups to have one or more of their pathologists register and participate in this critical webinar.

The roundtable discussion will help them understand how quickly AI-powered image analysis is expected be cleared for use by the FDA in such diseases as prostate cancer and melanomas. Both types of cancers generate high volumes of case referrals to the nation’s pathologists, so potential for disruption to long-standing client relationships, and the possible loss of revenue for pathology groups that delay their adoption of digital pathology, can be significant.

On the flip side, community pathology groups that jump on the digital pathology bandwagon early and with the right preparation will be positioned to build stronger client relationships, increase subspecialty case referrals, and generate additional streams of revenue that boost partner compensation within their group.

Act now to guarantee your place at this important webinar. Click HERE to register, or copy and paste the URL https://www.darkdaily.com/webinar/clinical-grade-artificial-intelligence-for-your-pathology-lab/ into your browser.

Also, because so many pathologists are working remotely, Dark Daily has arranged special group rates for pathology practices that would like their surgical pathologists to participate in this important webinar and roundtable discussion on AI-powered primary diagnosis of pathology images. Inquire at info@darkreport.com or call 512-264-7103.

—Michael McBride

Related Information:

Ibex Granted FDA Breakthrough Device Designation: Ibex’s Galen AI-powered platform is recognized by the FDA as breakthrough technology with the potential to more effectively diagnose cancer

Is Artificial Intelligence Ready for First Use in Anatomic Pathology?

Reducing Hospital Readmission: How Hospitals and Insurers are Making Strides

Oct 8, 2008 | Laboratory News, Laboratory Pathology

After discharge, almost one in six patients land back in the hospital due to complications that could have been prevented with better follow-up care! According to the Institute for Healthcare Improvement (IHI), nearly 18% of Medicare patients admitted to a hospital are readmitted within 30 days of discharge, accounting for $15 billion in spending, according to the Medicare Payment Advisory Commission http://www.medpac.gov/. Now, regulators, insurers, employers, and quality-measurement groups are all considering methods to tie hospitals’ payment to lower readmission rates.

“The experience of multiple hospitalizations can take a devastating toll on the human psyche and the quality of life for patients and their caregivers,” said Mary Naylor, a professor at the University of Pennsylvania School of Nursing. There are about 5 million readmissions a year in U.S. hospitals, with approximately a third occurring within 90 days of discharge. IHI research suggests that transitional care programs, which follow patients for varying periods of time at home, reduce admissions by up to 46%.

IHI is working with hospitals to reduce readmissions by: 1) identifying patients at risk for return; 2) scheduling follow-up doctor’s appointments before patients are discharged; 3) sending nurses to patients’ homes within a few days of discharge; 4) monitoring patients at home; and, 5) educating patients and families on how to adhere to medication schedules and self-care regimens. Part of the problem in getting hospitals to adopt these types of discharge programs in the past was that hospitals did not get paid to coordinate care after a patient left. That’s rapidly changing, now that large managed-care groups and insurers are experimenting with programs to cover such services.

Both Aetna and Kaiser Permanente unveiled pilot programs this year that focus on congestive heart failure patients, a third of which are generally readmitted within 30 days of discharge with complications from the condition. Early results from Kaiser’s program suggest success. Its two medical centers involved in the pilot program decreased their hospitalization and readmission rates for heart failure patients to about a third of Kaiser’s system-wide average.

A similar program developed at St. Luke’s Hospital in Cedar Rapids, Iowa, cut unplanned readmission rates in half, to 6%, as of last January. Prior to discharge, patients at St. Luke’s were asked to restate in their own words what they had been told about how to follow care instructions at home. These patients were then sent home with a refrigerator magnet that included a list of symptoms for which they should watch and an emergency number to call.

This emphasis on reducing readmission rates is no surprise to clients and regular readers of Dark Daily. The American healthcare system is actively looking to reduce medical errors, increase health outcomes, and at the same time cut the cost of care. Putting hospital readmission rates on the radar screen is consistent with this healthcare trend.

Further, the pay-for-performance dynamic makes sense. As the health insurer sees a reduction in costs because of a falling rate of hospital readmissions, it can pass these savings along to those hospitals in the form of pay-for-performance incentives or similar reimbursement arrangements. For the laboratory industry, the emphasis on reducing hospital readmission rates is a reminder that eventually pay-for-performance arrangements will arrive at the doorstep of laboratory medicine. Laboratories should be establishing internal performance measurements so they are prepared to document how their quality and efficiency improves over time.

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